Data Engineering & Analytics That Make Your Company AI-Ready

AI is only as good as the data under it. This is the unglamorous layer that decides whether anything else works.

1

warehouse, one definition per metric, one number in every meeting

Prereq

data quality and access are the top blocker for enterprise AI agents

Source: 2026 agentic AI research

Daily

automated refresh instead of manual exports at 11pm

The reason you’re here

Sound familiar?

  • Sales, finance and ops each report a different revenue number for the same month.
  • Your dashboard is a screenshot in a slide deck, updated by hand.
  • Data sits in five SaaS tools and nobody can join them.
  • Every AI vendor tells you your data is not ready. They are usually right.
  • Queries that took two seconds last year now take four minutes.

Every one of those is a solved problem. Below is exactly how we solve it, what it costs you in time, and what you get to keep at the end.

What you get

Data Engineering & Analytics, delivered as concrete pieces of work

Source audit & metric dictionary

Every system inventoried and every metric defined once, in writing, with an owner. This is where the arguing stops.

Ingestion pipelines

Scheduled and streaming ingestion from your ERP, CRM, app database, payment gateways and SaaS tools — with retries and alerting.

Warehouse & modelling

Postgres, BigQuery or ClickHouse, modelled with dbt so transformations are versioned, tested and reviewable.

Dashboards people use

Metabase, Power BI or a custom app — role-scoped, fast, and answering the questions leadership actually asks on Sunday.

AI-ready serving layer

Clean, permissioned, embedded data that agents and copilots can query safely. The groundwork for every automation project.

Quality monitoring

Freshness, volume and schema tests that page someone when a feed goes quiet — before the board deck does.

How we work

Small first step. Measured result. Then scale.

  1. 1 · Inventory

    Every source, owner, refresh rate and known lie in the current numbers.

  2. 2 · Model

    Warehouse schema and dbt models for the ten metrics that matter most.

  3. 3 · Serve

    Dashboards and APIs on top, with access control matched to your org chart.

  4. 4 · Trust

    Tests, alerts and documentation so the numbers keep being right when we are not looking.

Questions we get asked

Before you email us

We are not a big company. Do we need a warehouse?

If your data fits comfortably in one production database and one tool, no — and we will say so rather than sell you infrastructure. It becomes worth it once three or more systems have to be joined, or once reporting queries start competing with your live app.

Can you work with our existing BI tool?

Yes. Power BI, Tableau, Metabase, Looker Studio — the modelling layer is what matters, and it stays portable across whichever front end you keep.

How does this connect to AI?

Directly. Agents and copilots are only as reliable as the data they retrieve. A clean, permissioned serving layer is usually the difference between an AI pilot that ships and one that quietly gets shelved.

Start here

Tell us what’s broken. We’ll tell you what it takes to fix it.

You get a 30-minute call with an engineer — not a salesperson — and a written summary of the approach, rough timeline and rough cost. No obligation, no drip campaign.

  • Reply within one business day
  • Fixed-price milestones after discovery
  • You own the source code, always
  • NDA before the first call if you want one

Prefer email? [email protected] · +880 1635 191148

Get a data engineering & analytics proposal

Two minutes to fill in. A real answer back, from someone who will do the work.

No sales sequence. One human reply with a concrete next step, usually within a business day.